Composition of glaciar sediments from the Aar massif (Switzerland)
Blood samples
Activity patterns of a statistician for 20 days
Color-size compositions of 20 clam colonies from East Bay
Permeabilities of bayesite
Activity patterns of a statistician for 20 days
Animal and vegetation measurement
Compositions and depth of 25 specimens of boxite
Artic lake sediment samples of different water depth
Color-size compositions of 20 clam colonies from West Bay
Compositions, depths and porosities of 25 specimens of coxite
Household Expenditures
Steroid metabolite patterns in adults and children
Helper to compute confidence ellipsoids
Compositions of 25 specimens of kongite
Compositional Linear Model of Coregionalisation
White-cell composition of 30 blood samples by two different methods
Diagnostic probabilities
Proportions of supervisor's statements assigned to different categories
Count compositions
Hydrochemical composition data set of Llobregat river basin water (NE Spain)
Compositional Goodness of fit test
Firework mixtures
A biplot providing somewhat easier access to details of the plot.
Honk Kong Pogo-Jumps Championship
Compositions and total pebble counts of 92 glacial tills
R square
Yatquat fruit evaluation
Measurement of skulls
Bar charts of amounts
Aitchison compositions
Create a color/char palette or for groups of outliers
compositions
Treating binary and g-adic numbers
Correlations of amounts and compositions
Heuristics to find subpopulations of outliers
Dendrogram representation of acomp or rcomp objects
AFM compositions of 23 aphyric Skye lavas
Compositions of 25 specimens of hongite
An auxiliary functions to compute user-defined ilr and ipt transforms.
Internal function: row and column sums of matrices
Internal functions of the compositions package
Interal function: Get number of samples and number of parts in a compositional object
Proportions of sand, silt and clay in sediments specimens
Serum Protein compositions of blood samples
Internal functions of the compositions package
Compositional Ordinary Kriging
Internal function: Convert to plain vector or matrix
The policy of treatment of missing values in the "compositions" package
Marginal compositions in Aitchison Compositions
Compute balances for a compositional dataset.
Power transform in the simplex
Drawing a 3D coordiante system to a plot, based on package rgl
Fitting a Dirichlet distribution
Isometric identity transform
Isometric log ratio transform
Hotellings T square distribution
Shifts of machine operators
fitSameMeanDifferentVarianceModel
Fit Same Mean Different Variance Model
Internal function: give a derived subclass to an object
The geometric mean
Classical Gauss Test
Internal functions: Parallel operations of single and multiple datasets
Isometric planar transform
Check for compositional data type
The arithmetic mean of rows or columns
Mean amounts and mean compositions
Simulated amount datasets
Additive log ratio transform
vectorial arithmetic for data sets with aplus class
Internal functions: A conditional drop
Perturbation of compositions
Group amounts of parts
Amounts analysed in log-scale
power transform of a matrix
Ternary diagrams
Three-dimensional biplots, based on package rgl
The canonical basis in the clr plane used for ilr and ipt transforms.
arrows in 3D, based on package rgl
Additive planar transform
Convert "compositions" classes to data frames
Centered log ratio transform
Displaying compositions and amounts with box-plots
Convert between clr and ilr, and between cpt and ipt.
Principal component analysis for amounts in log geometry
Principal component analysis for Aitchison compositions
Environment containing the old gsi functions
Internal functions of the compositions package
Internal functions of the compositions package
Internal functions of the compositions package
Internal function: Recode missings with IEEE number and vice versa
Principal component analysis for real compositions
Treating single compositions as one-row datasets
plot in 3D based on rgl
Detect and classify compositional outliers.
Internal function: Invert a permutation
Normal quantile plots for compositions and amounts
vectorial arithmetic for datasets in a classical vector scale
3D-plot of compositional data
Dirichlet distribution
inner product for datasets with vector scale
Centered default transform
Internal function: Checking equality of IEEE special numbers
Centered planar transform
Distances in variouse approaches
Internal function: Can something be considered as a single
multivariate data item?
Closure of a composition
Internal functions: Storing integers as reals
Internal function: computes variance of compositional data set with missing/zero values
Isometric default transform
Recast amounts as mixtures of end-members
Draw ellipses
Gets the detection limit stored in the data set
Simulate count compositions without overdispersion
vgram2lrvgram
The uniform distribution on the simplex
Compositional Goodness of fit test
Internal function: Scaling rcomp
Isometric log transform
Calling from a function with the own parameters
The canonical basis in the clr plane used for ilr and ipt transforms.
Marginal compositions in real geometry
Draws straight lines from point to point.
Reads a data file in a geoeas format
Ternary diagrams
Internal function: Compute a desired compositional margin
Internal function: Reshape an object to the shape type of another
Auxiliary functions to compute user-defined ilr and ipt transforms.
Internal functions of the compositions package
Checking for outliers
Isoportion- and Isoproportion-lines
Compute Mahalanobis distances based von robust Estimations
Draws connected lines from point to point.
Reads a data file in a mixR format
transformations from 'mixtures' to 'compositions' classes
Transformations from 'mixtures' to 'compositions' classes
Internal functions: Generate a diagonal matrix
Internal function: Solves singular and non square equation systems
Internal functions of the compositions package
Internal functions: Get the diagonal of a matrix
Plot a Missing Summary
Internal function: A panel displaying a label only
Internal functions of the compositions package
Displaying amounts in scatterplots
Empirical variograms for compositions
Returns a projector the the observed space in case of missings.
Vector space norm
Principal component analysis for real data
3D-plot of positive data
plot in 3D based on rgl
Principal component analysis for real amounts
Normalize vectors to norm 1
Classify and summarize missing values in a dataset
Compositional Goodness of fit test
Summaries of amounts
Summary of compositions in real geometry
Variance covariance matrix of parameters in compositional regression
Aitchison Distribution
The names of the parts
Empirical variograms for compositions
Unique parametrisations for matrices.
Plots of pairwise logratio against a covariable.
Printing compositional data.
Metric summary statistics of real, amount or compositional data
Parallel scalar products
plot in 3D based on rgl
Creates a paneled plot like pairs for two different datasets.
Compute distributions of empirical Mahalanobis distances based on
simulations
Loadings of relations of two amounts
Compute the global projector to the observed subspace.
Variogram functions
Residual variance of a model
Axis for ternary diagrams
Simple treatment of real vectors
Compositional variogram model fitting
The jura dataset
inner product for datasets with a vector space structure
Ploting composition into rotable tetrahedron
inner product for matrices and vectors
Total sum of amounts
Modify parameters of compositional plots.
The multivariate lognormal distribution
Analysing outliers in compositions.
Plot various graphics to analyse outliers.
Compositions as elements of the simplex embedded in the D-dimensional real space
Arithmetic operations for compositions in a real geometry
Normalizing datasets by centering and scaling
Draws straight lines.
Summarizing a compositional dataset in terms of ratios
Normal distributions on special spaces
Zero-replacement routine
vectorial arithmetic for data sets with rplus class
Uncentered log transform
Amounts i.e. positive numbers analysed as objects of the real vector space
Empirical variograms for compositions
Splitting datasets in groups given by factors
Variation matrices of amounts and compositions
Variances and covariances of amounts and compositions
Artifical simulation of various kinds of missings/polluted data
Handling robustness issues and outliers in compositions.